Tiefenkartenbasierte Superresolution f ür 3D-Rekonstruktion

Projecte realitzat en el marc d’un programa de mobilitat amb la Fakultät für Informätik de la Technischen Universität MünchenIn this thesis a superresolution method consisting in a deblurring and an upsampling is used to improve the quality of a 3D reconstruction using data sampled with a Kinect. Results show that there is a significant quality improve

Tiefenkartenbasierte Superresolution f ür 3D-Rekonstruktion

Projecte realitzat en el marc d’un programa de mobilitat amb la Fakultät für Informätik de la Technischen Universität MünchenIn this thesis a superresolution method consisting in a deblurring and an upsampling is used to improve the quality of a 3D reconstruction using data sampled with a Kinect. Results show that there is a significant quality improve

Tiefenkartenbasierte Superresolution f ür 3D-Rekonstruktion

Projecte realitzat en el marc d’un programa de mobilitat amb la Fakultät für Informätik de la Technischen Universität MünchenIn this thesis a superresolution method consisting in a deblurring and an upsampling is used to improve the quality of a 3D reconstruction using data sampled with a Kinect. Results show that there is a significant quality improve

Standard quasi-conformal flattening of the right and left atria

Two-dimensional standard representations of 3D anatomical structures are a simple and intuitive way for analysing patient information across populations and image modalities. They also allow convenient visualizations that can be included in clinical reports for a fast overview of the whole structure. While cardiac ventricles, especially the left ventricle, have an established standard representation (e.g. bull’s eye plot), the 2D depiction of the left (LA) and right atrium (RA) remains challenging due to their sub-structural complexity. Quasi-conformal flattening techniques, successfully applied to cardiac ventricles, require additional constraints in the case of the atria to correctly place the adjacent structures, i.e. the pulmonary veins, the vena cava (VC) or the appendages. Some registration-based methods exist to flatten the LA but they can be time-consuming and prone to errors if the geometries are very different. We propose a novel atrial flattening methodology where a quasi-conformal 2D map of both (left and right) atria is obtained quickly and without errors related to registration. In our approach the RA is mapped to a standard 2D map where the holes corresponding to superior and inferior VC are fixed within a disk. Similarly, the LA is divided into 5 regions which are then mapped to their analogous two-dimensional regions. We illustrate the application of the method to visualize atrial wall thickness measurements, and late gadolinium enhanced magnetic resonance data.This study was partially funded by the Spanish Ministry of Economy and Competitiveness (DPI2015-71640-R), by the “Fundació La Marató de TV3” (no 20154031) and by European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)

Fast quasi-conformal regional flattening of the left atrium

Two-dimensional representation of 3D anatomical structures is a simple and intuitive way for analysing patient information across populations and image modalities. While cardiac ventricles, especially the left ventricle, have an established standard representation (bull's eye plot), the 2D depiction of the left atrium (LA) remains challenging due to its sub-structural complexity including the pulmonary veins (PV) and the left atrial appendage (LAA). Quasi-conformal flattening techniques, successfully applied to cardiac ventricles, require additional constraints in the case of the LA to place the PV and LAA in the same geometrical 2D location for different cases. Some registration-based methods have been proposed but surface registration is time-consuming and prone to errors when the geometries are very different. We propose a novel atrial flattening methodology where a 2D standardised map of the LA is obtained quickly and without errors related to registration. The LA is divided into five regions which are then mapped to their analogue two-dimensional regions. 67 human left atria from magnetic resonance images (MRI) were studied to derive a population-based template representing the averaged relative locations of the PVs and LAA. The clinical application of our methodology is illustrated on different use cases including the integration of MRI and electroanatomical data.This study was partially funded by the Spanish Ministry of Economy and Competitiveness (DPI2015-71640-R), by the “Fundació La Marató de TV3” (no20154031) and by European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)

Reinforcement learning for active modality selection during diagnosis

Comunicació presentada a 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022), celebrat del 18 al 22 de setembre de 2022 a Sentosa, Singapur.Diagnosis through imaging generally requires the combination of several modalities. Algorithms for data fusion allow merging information from different sources, mostly combining all images in a single step. In contrast, much less attention has been given to the incremental addition of new data descriptors, and the consideration of their costs (which can cover economic costs but also patient comfort and safety). In this work, we formalise clinical diagnosis of a patient as a sequential process of decisions, each of these decisions being whether to take an additional acquisition, or, if there is enough information, to end the examination and produce a diagnosis. We formulate the goodness of a diagnosis process as a combination of the classification accuracy minus the cost of the acquired modalities. To obtain a policy, we apply reinforcement learning, which recommends the next modality to incorporate based on data acquired at previous stages and aiming at maximising the accuracy/cost trade-off. This policy therefore performs medical diagnosis and patient-wise feature selection simultaneously. We demonstrate the relevance of this strategy on two binary classification datasets: a subset of a public heart disease database, including 531 instances with 11 scalar features, and a private echocardiographic dataset including signals from 5 standard image sequences used to assess cardiac function (2 speckle tracking, 2 flow Doppler and tissue Doppler), from 188 patients suffering hypertension, and 60 controls. For each individual, our algorithm allows acquiring only the modalities relevant for the diagnosis, avoiding low-information acquisitions, which both resulted in higher stability of the chosen modalities and better classification performance under a limited budget.The authors acknowledge the partial support from the French ANR (LABEX PRIMES of Univ. Lyon [ANR-11-LABX-0063] and the JCJC project “MIC-MAC” [ANR-19-CE45-0005]) and the Spanish AEI [PID2019-108141GB-I00]

Assessment of haemodynamic remodeling in fetal aortic coarctation using a lumped model of the circulation

Comunicació presentada a: the 9th International Conference Functional Imaging and Modelling of the Heart FIMH 2017, celebrat de l'11 al 13 de juny de 2017 a Toronto, Canadà.Aortic coarctation is one of the most difficult cardiac defects to diagnose before birth, and it accounts for 8% of congenital heart diseases. Antenatal diagnosis is crucial for early treatment of the neonate and to decrease the risk of morbidity and mortality; however the fetal hemodynamic changes are not fully understood and current imaging methods are limited to accurately diagnosis this congenital defect. Objective: We propose to use a lumped model of the fetal circulation to provide insights into the hemodynamic changes in fetuses with aortic coarctation, and thus helping to improve its diagnosis. Methods: To achieve this goal a patient-specific lumped model of the fetal circulation was implemented in OpenCOR, including the modeling of different types and degrees of aortic coarctation. A parametric study of degree and type of coarctation was performed, where blood flow distribution, cerebroplacental ratio, pressure drop over the coarctation and left ventricular pressure were quantified. Results: Obvious changes in the fetal hemodynamics were observed only from 80% of coarctation, corresponding to the clinically used cutoff for pressure drop of 20 mmHg. Furthermore, the observed hemodynamic changes were different depending on the location and degree of the coarctation.This study was partially supported by the Spanish Ministry of Economy and Competitiveness (grant TIN2014-52923-R; Maria de Maeztu Units of Excellence Programme - MDM-2015-0502), FEDER and the European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)

Assessment of haemodynamic remodeling in fetal aortic coarctation using a lumped model of the circulation

Comunicació presentada a: the 9th International Conference Functional Imaging and Modelling of the Heart FIMH 2017, celebrat de l'11 al 13 de juny de 2017 a Toronto, Canadà.Introduction: Aortic coarctation is one of the most difficult cardiac defects to diagnose before birth, and it accounts for 8% of congenital heart diseases. Antenatal diagnosis is crucial for early treatment of the neonate and to decrease the risk of morbidity and mortality; however the fetal hemodynamic changes are not fully understood and current imaging methods are limited to accurately diagnosis this congenital defect. Objective: We propose to use a lumped model of the fetal circulation to provide insights into the hemodynamic changes in fetuses with aortic coarctation, and thus helping to improve its diagnosis. Methods: To achieve this goal a patient-specific lumped model of the fetal circulation was implemented in OpenCOR, including the modeling of different types and degrees of aortic coarctation. A parametric study of degree and type of coarctation was performed, where blood flow distribution, cerebroplacental ratio, pressure drop over the coarctation and left ventricular pressure were quantified. Results: Obvious changes in the fetal hemodynamics were observed only from 80% of coarctation, corresponding to the clinically used cutoff for pressure drop of 20 mmHg. Furthermore, the observed hemodynamic changes were different depending on the location and degree of the coarctation.This study was partially supported by the Spanish Ministry of Economy and Competitiveness (grant TIN2014-52923-R; Maria de Maeztu Units of Excellence Programme - MDM-2015-0502), FEDER and the European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)

Estimating 3D ventricular shape from 2D echocardiography: feasibility and effect of noise

Comunicació presentada a la 9th international conference on Functional Imaging and Modeling of the Heart (FIMH 2017), celebrada els dies 11 a 13 de juny de 2017 a Toronto, Canadà.Many cardiac diseases are associated with changes in ventricular shape. However, in daily practice, the heart is mostly assessed by 2D echocardiography only. While 3D techniques are available, they are rarely used. In this paper we analyze to which extent it is possible to obtain the 3D shape of a left ventricle (LV) using measurements from 2D echocardiography. First, we investigate this using synthetic datasets, and afterwards, we illustrate it in clinical 2D echocardiography measurements with corresponding 3D meshes obtained using 3D echocardiography. We demonstrate that standard measurements taken in 2D allow quantifying only the ellipsoidal shape of the ventricle, and that capturing other shape features require either additional geometrical measurements or clinical information related to shape remodelling. We show that noise in the measurements is the primary cause for poor association between the measurements and the LV shape features and that an estimated 10% level of noise on the 2D measurements limits the recoverability of shape. Finally we show that clinical variables relating to the clinical history can substitute the lack of geometric measurements, thus providing alternatives for shape assessment in daily practice.This study was partially supported by the Spanish Ministry of Economy and Competitiveness (grant TIN2014-52923-R; Maria de Maeztu Units of Excellence Programme - MDM-2015-0502), FEDER and the European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)

A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts

Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the endocardium of the right ventricle, the interventricular septum and the outflow tracts. We also carried out electrophysiological simulations involving these structures and with different fiber configurations. In particular, we built a modelling pipeline for creating patient-specific volumetric meshes of biventricular geometries, including the outflow tracts, and subsequently simulate the electrical wavefront propagation in outflow tract ventricular arrhythmias with different origins for the ectopic focus. The resulting simulations with the proposed rule-based method showed a very good agreement with clinical parameters such as the 10 ms isochrone ratio in a cohort of nine patients suffering from this type of arrhythmia. The developed modelling pipeline confirms its potential for an in silico identification of the site of origin in outflow tract ventricular arrhythmias before clinical intervention.This work was partially funded by the European Union under the Horizon 2020 Programme for Research, Innovation (grant agreement No. 642676 CardioFunXion)